anniversary 发表于 2025-3-28 15:04:42
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Leveraging Semantic Segmentation Masks with Embeddings for Fine-Grained Form Classificationssification is impractical for large collections due to its labor-intensive and error-prone nature. To address this, we propose a representational learning strategy that integrates semantic segmentation and deep learning models such as ResNet, CLIP, Document Image Transformer (DiT), and masked auto-胎儿 发表于 2025-3-29 00:42:57
DocLightDetect: A New Algorithm for Occlusion Classification in Identification Documentsin the physical realm raises significant challenges. Several entities, including financial institutions, insurance companies, and government services, require photos of documents sent through mobile applications to associate the physical and digital personas. This procedure entails significant compuHEPA-filter 发表于 2025-3-29 06:05:17
Confidence-Aware Document OCR Error Detection utility of OCR confidence scores for enhancing post-OCR error detection. Our study involves analyzing the correlation between confidence scores and error rates across different OCR systems. We develop ConfBERT, a BERT-based model that incorporates OCR confidence scores into token embeddings and offGrating 发表于 2025-3-29 10:09:12
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oring of handwritten short descriptive answers in Japanese language exams. We used a deep neural network (DNN)-based handwriting recognizer and a transformer-based automatic scorer without correcting misrecognized characters or adding rubric annotations for scoring. We achieved acceptable agreementLimpid 发表于 2025-3-29 16:42:53
https://doi.org/10.1007/978-1-349-06578-3n. This technological intervention can help streamline and standardize the decision-making process across all levels of courts. One key benefit of developing such a system is that the junior judges can benefit from the collective knowledge stored in the knowledge base, improving their ability to mak痛打 发表于 2025-3-29 23:11:52
o the coexistence of signatures with other textual and graphical elements on real-world documents. Verification systems must first detect the signature and then validate its authenticity, a dual challenge often overlooked by current datasets and methodologies focusing only on verification. To addresIndelible 发表于 2025-3-30 00:09:51
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e-Vision (LV) models for document analysis and predictions on document images, respectively. Usually, deep neural networks for the DocVQA task are trained on datasets lacking instructions. We show that using instruction-following datasets improves performance. We compare performance across document-